Gong Yuda, Liu Xuan, Sahu Arvind, Reddy Abhinav V, Wang Haiyu
Department of General Surgery, Fudan University Zhongshan Hospital, Shanghai, China.
Department of Oncology, Goulburn Valley Health, Shepparton, Victoria, Australia.
Ann Transl Med. 2022 Aug;10(15):834. doi: 10.21037/atm-22-3530.
Gastric cancer (GC) is the 5th most common cause of cancer in the world and the 3rd largest cause of cancer-related death. It is usually associated with a variety of cancers, of which cholangiocarcinoma (CCA) combined with GC accounts for about 1.6%. This study sought to examine the hub genes and role of lipid metabolism in the development and diagnosis of GC and CCA.
To screen potential hub genes, The Cancer Genome Atlas (TCGA) data sets, including the GC (STAD, dataset of GC) and CCA (CHOL, dataset of CCA) data sets, were used to conduct a differentially expressed gene (DEG) analysis and an enrichment analysis of the DEGs. A weighted-gene co-expression network analysis (WGCNA) was conducted to identify the significant gene module and then find the hub genes in the module. To verify the 4 hub genes, we conducted a differentiation analysis of the 4 genes in GC and CCA and found that there were differences. A survival analysis of the hub genes was performed and mutations were mapped. Additionally, tumor immune microenvironment (TIME) and immune analyses were performed to evaluate how lipid metabolism affects the development of GC with CCA.
The principal component analysis showed that both GC and CCA had distinct up-regulated and down-regulated genes, which are involved in a variety of metabolic processes. Upon WGCNA, the turquoise and blue modules were meaningful, and the hub genes were identified from these 2 modules. Four hub genes were identified: amyloid beta precursor protein binding family B member 1 (), Homo sapiens armadillo repeat containing X-linked 1 (), DAZ interacting zinc finger protein 1 (), and methionine sulfoxide reductase B3 (). In survival analysis, increased expression of the 4 hub genes was associated with inferior survival outcomes, with variations in all 4 genes. Additionally, we demonstrated that genes related to lipid metabolism had an effect on immune function.
, , , and affect the development of GC and CCA and can be used as biomarkers. The expression of lipid metabolism genes is related to the TIME of patients with GC and CCA.
胃癌（GC）是全球第5大常见癌症，也是癌症相关死亡的第3大原因。它通常与多种癌症相关，其中胆管癌（CCA）合并GC约占1.6%。本研究旨在探讨枢纽基因以及脂质代谢在GC和CCA发生发展及诊断中的作用。
为筛选潜在的枢纽基因，利用癌症基因组图谱（TCGA）数据集，包括GC（STAD，GC数据集）和CCA（CHOL，CCA数据集）数据集，进行差异表达基因（DEG）分析和DEG的富集分析。进行加权基因共表达网络分析（WGCNA）以识别显著基因模块，然后在该模块中找到枢纽基因。为验证这4个枢纽基因，我们对GC和CCA中的这4个基因进行了差异分析，发现存在差异。对枢纽基因进行生存分析并绘制突变图谱。此外，进行肿瘤免疫微环境（TIME）和免疫分析，以评估脂质代谢如何影响GC合并CCA的发生发展。
主成分分析表明，GC和CCA均有明显上调和下调的基因，这些基因参与多种代谢过程。通过WGCNA，绿松石色和蓝色模块有意义，并从这2个模块中鉴定出枢纽基因。鉴定出4个枢纽基因：淀粉样前体蛋白结合家族B成员1（ ）、含犰狳重复序列的X连锁1（ ）、DAZ相互作用锌指蛋白1（ ）和甲硫氨酸亚砜还原酶B3（ ）。在生存分析中，这4个枢纽基因表达增加与较差的生存结果相关，且所有4个基因均有变异。此外，我们证明与脂质代谢相关的基因对免疫功能有影响。
、 、 和 影响GC和CCA的发生发展，可作为生物标志物。脂质代谢基因的表达与GC和CCA患者的TIME相关。
